The following abbreviations are herewith defined, at least some of which are referred to within the following description of the prior art and the present invention.    DPI Deep Packet Inspection    HTTP Hypertext Transfer Protocol    ISP Internet Service Providers    P2P Peer-to-peer    QoS Quality of Service    RAN Radio Access Network    RNC Radio Network Controller    SMTP Simple Mail Transfer Protocol    TCP/IP Transmission Control Protocol/Internet Protocol
In-depth understanding of a profile for Internet traffic is a challenging task for researchers and a mandatory requirement for most Internet Service Providers (ISP). To this end, Deep Packet Inspection (DPI) tools help ISPs in the quest for profiling networked applications. With this information in hand, ISPs may then apply different charging policies, traffic shaping, and offer different QoS guarantees to selected users or applications.
DPI tools search the traffic in a stateless manner for frequently occurring protocol fragments referred to in the art as signatures to recognize a specific application in a data stream. DPI tools can be tested in terms of accuracy as well as performance, where accuracy is the ratio of well-classified traffic and the total traffic of a specific application and performance shows the number of tested signatures for a given size (specific bandwidth) of traffic in a fix period of time. In this regard, it is well known that increasing accuracy by adding more and more signatures to the application-signature database negatively affects performance. The goal of the developers of DPI tools is to provide high enough accuracy in real world telecommunication networks with the highest possible performance.
The best solution to help meet this goal is to enable DPI tools to use measurements from a real telecommunications network, but the network data is the property of the operator and there are plenty of privacy issues can arise. As such, the most common solution used today for meeting this goal is to enable DPI tools to use measurements from user traffic simulators which mimic several application level network protocols (e.g., HTTP, SMTP), transport layer network protocols (e.g., TCP/IP), and user behavior (e.g., Poisson arrival). However, simulators are not very flexible. For instance, simulators can only mimic extreme scenarios e.g., when the transport network utilizes the full bandwidth or when the packets arrive with a limited speed. In practice, the traffic is more elastic and difficult to simulate when compared to real world scenarios. Plus, simulators can only simulate such traffic which is encoded in them and to create up-to-date traffic the simulator has to be updated with the most up-to-date signatures. To this end, the simulator would practically need to know the whole protocol and replay the protocol to create valid conversations between the network parties. This whole process is an overhead which can be saved if the DPI tools could use measurements (validation traces) obtained by using real protocols in a real network environment. Thus, there is a need for a system that can provide an in-depth understanding of a traffic profile by constructing a validation trace (i.e., high-speed realistic network traffic) using a real network without causing privacy concerns. This need and other needs are satisfied by the system and method of the present invention.